Simulation study of multiple intelligent vehicle control using stochastic learning automata

This paper presents an intelligent controller for an automated vehicle planning its trajectory based on sensor and communication data received. The controller is designed using a stochastic learning automaton. Using the data received from on-board sensors, two automata are capable of learning the best possible actions to avoid collisions. Simulations for simultaneous lateral and longitudinal control of a vehicle using this method are encouraging.

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